{
 "cells": [
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# Example of AuthorTopicModel "
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "\"The Author-Topic Model for Authors and Documents\" by Rosen-Zvi, et al. (UAI 2004)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 1,
   "metadata": {
    "collapsed": false
   },
   "outputs": [],
   "source": [
    "import pickle\n",
    "import logging\n",
    "\n",
    "import numpy as np\n",
    "import matplotlib\n",
    "import matplotlib.pyplot as plt\n",
    "\n",
    "from ptm import AuthorTopicModel\n",
    "from ptm.utils import convert_cnt_to_list, get_top_words\n",
    "\n",
    "logger = logging.getLogger('AuthorTopicModel')\n",
    "logger.propagate=False\n",
    "\n",
    "%matplotlib inline"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Load CORA dataset"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "The original dataset from: https://people.cs.umass.edu/~mccallum/data.html"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "metadata": {
    "collapsed": false
   },
   "outputs": [],
   "source": [
    "doc_ids = pickle.load(open('../data/cora/doc_ids.pkl', 'rb'))\n",
    "doc_cnt = pickle.load(open('../data/cora/doc_cnt.pkl', 'rb'))\n",
    "doc_author = pickle.load(open('../data/cora/doc_authorid.pkl', 'rb'))\n",
    "author_name = pickle.load(open('../data/cora/authorid_authorname.pkl', 'rb'))\n",
    "voca = pickle.load(open('../data/cora/voca.pkl', 'rb'))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "metadata": {
    "collapsed": false
   },
   "outputs": [],
   "source": [
    "corpus = convert_cnt_to_list(doc_ids, doc_cnt)\n",
    "n_doc = len(corpus)\n",
    "n_topic = 10\n",
    "n_author = len(author_name)\n",
    "n_voca = len(voca)\n",
    "max_iter = 50"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Fit author-topic model"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "2016-02-14 22:04:27 INFO:AuthorTopicModel:[INIT] 0\telapsed_time:63.54\tlog_likelihood:-10863554.38\n",
      "2016-02-14 22:05:30 INFO:AuthorTopicModel:[INIT] 1\telapsed_time:63.58\tlog_likelihood:-10647481.99\n",
      "2016-02-14 22:06:34 INFO:AuthorTopicModel:[INIT] 2\telapsed_time:63.74\tlog_likelihood:-10492422.12\n",
      "2016-02-14 22:07:38 INFO:AuthorTopicModel:[INIT] 3\telapsed_time:63.77\tlog_likelihood:-10357087.07\n",
      "2016-02-14 22:08:40 INFO:AuthorTopicModel:[INIT] 4\telapsed_time:62.19\tlog_likelihood:-10229123.70\n",
      "2016-02-14 22:09:35 INFO:AuthorTopicModel:[INIT] 5\telapsed_time:54.96\tlog_likelihood:-10096179.15\n",
      "2016-02-14 22:10:30 INFO:AuthorTopicModel:[INIT] 6\telapsed_time:54.89\tlog_likelihood:-9943646.09\n",
      "2016-02-14 22:11:25 INFO:AuthorTopicModel:[INIT] 7\telapsed_time:54.84\tlog_likelihood:-9769853.39\n",
      "2016-02-14 22:12:22 INFO:AuthorTopicModel:[INIT] 8\telapsed_time:57.85\tlog_likelihood:-9598314.53\n",
      "2016-02-14 22:13:23 INFO:AuthorTopicModel:[INIT] 9\telapsed_time:60.43\tlog_likelihood:-9453899.31\n",
      "2016-02-14 22:14:22 INFO:AuthorTopicModel:[INIT] 10\telapsed_time:59.53\tlog_likelihood:-9338106.69\n",
      "2016-02-14 22:15:21 INFO:AuthorTopicModel:[INIT] 11\telapsed_time:58.89\tlog_likelihood:-9244523.47\n",
      "2016-02-14 22:16:21 INFO:AuthorTopicModel:[INIT] 12\telapsed_time:59.88\tlog_likelihood:-9173893.80\n",
      "2016-02-14 22:17:23 INFO:AuthorTopicModel:[INIT] 13\telapsed_time:61.79\tlog_likelihood:-9116831.15\n",
      "2016-02-14 22:18:24 INFO:AuthorTopicModel:[INIT] 14\telapsed_time:61.34\tlog_likelihood:-9068511.26\n",
      "2016-02-14 22:19:24 INFO:AuthorTopicModel:[INIT] 15\telapsed_time:59.51\tlog_likelihood:-9030260.41\n",
      "2016-02-14 22:20:26 INFO:AuthorTopicModel:[INIT] 16\telapsed_time:61.86\tlog_likelihood:-8996108.24\n",
      "2016-02-14 22:21:27 INFO:AuthorTopicModel:[INIT] 17\telapsed_time:61.55\tlog_likelihood:-8964674.92\n",
      "2016-02-14 22:22:31 INFO:AuthorTopicModel:[INIT] 18\telapsed_time:63.73\tlog_likelihood:-8941120.13\n",
      "2016-02-14 22:23:34 INFO:AuthorTopicModel:[INIT] 19\telapsed_time:63.34\tlog_likelihood:-8921381.73\n",
      "2016-02-14 22:24:36 INFO:AuthorTopicModel:[INIT] 20\telapsed_time:61.47\tlog_likelihood:-8903072.00\n",
      "2016-02-14 22:25:37 INFO:AuthorTopicModel:[INIT] 21\telapsed_time:60.91\tlog_likelihood:-8886887.71\n",
      "2016-02-14 22:26:39 INFO:AuthorTopicModel:[INIT] 22\telapsed_time:62.48\tlog_likelihood:-8872823.62\n",
      "2016-02-14 22:27:43 INFO:AuthorTopicModel:[INIT] 23\telapsed_time:63.59\tlog_likelihood:-8856336.04\n",
      "2016-02-14 22:28:47 INFO:AuthorTopicModel:[INIT] 24\telapsed_time:63.87\tlog_likelihood:-8845108.89\n",
      "2016-02-14 22:29:49 INFO:AuthorTopicModel:[INIT] 25\telapsed_time:62.69\tlog_likelihood:-8834276.61\n",
      "2016-02-14 22:30:49 INFO:AuthorTopicModel:[INIT] 26\telapsed_time:59.47\tlog_likelihood:-8823068.52\n",
      "2016-02-14 22:31:50 INFO:AuthorTopicModel:[INIT] 27\telapsed_time:61.48\tlog_likelihood:-8814344.53\n",
      "2016-02-14 22:32:50 INFO:AuthorTopicModel:[INIT] 28\telapsed_time:59.72\tlog_likelihood:-8806725.65\n",
      "2016-02-14 22:33:49 INFO:AuthorTopicModel:[INIT] 29\telapsed_time:58.68\tlog_likelihood:-8799515.99\n",
      "2016-02-14 22:34:50 INFO:AuthorTopicModel:[INIT] 30\telapsed_time:61.03\tlog_likelihood:-8792988.33\n",
      "2016-02-14 22:35:50 INFO:AuthorTopicModel:[INIT] 31\telapsed_time:59.95\tlog_likelihood:-8787366.00\n",
      "2016-02-14 22:36:52 INFO:AuthorTopicModel:[INIT] 32\telapsed_time:62.10\tlog_likelihood:-8780941.95\n",
      "2016-02-14 22:37:55 INFO:AuthorTopicModel:[INIT] 33\telapsed_time:62.92\tlog_likelihood:-8776050.13\n",
      "2016-02-14 22:38:57 INFO:AuthorTopicModel:[INIT] 34\telapsed_time:62.04\tlog_likelihood:-8771034.29\n",
      "2016-02-14 22:39:56 INFO:AuthorTopicModel:[INIT] 35\telapsed_time:59.79\tlog_likelihood:-8763705.60\n",
      "2016-02-14 22:40:57 INFO:AuthorTopicModel:[INIT] 36\telapsed_time:60.35\tlog_likelihood:-8759335.53\n",
      "2016-02-14 22:41:56 INFO:AuthorTopicModel:[INIT] 37\telapsed_time:58.78\tlog_likelihood:-8755129.16\n",
      "2016-02-14 22:42:54 INFO:AuthorTopicModel:[INIT] 38\telapsed_time:58.65\tlog_likelihood:-8754418.15\n",
      "2016-02-14 22:43:51 INFO:AuthorTopicModel:[INIT] 39\telapsed_time:56.47\tlog_likelihood:-8747837.15\n",
      "2016-02-14 22:44:49 INFO:AuthorTopicModel:[INIT] 40\telapsed_time:58.43\tlog_likelihood:-8743544.53\n",
      "2016-02-14 22:45:50 INFO:AuthorTopicModel:[INIT] 41\telapsed_time:60.66\tlog_likelihood:-8738763.21\n",
      "2016-02-14 22:46:51 INFO:AuthorTopicModel:[INIT] 42\telapsed_time:61.46\tlog_likelihood:-8733850.16\n",
      "2016-02-14 22:47:54 INFO:AuthorTopicModel:[INIT] 43\telapsed_time:63.01\tlog_likelihood:-8733093.74\n",
      "2016-02-14 22:48:51 INFO:AuthorTopicModel:[INIT] 44\telapsed_time:56.68\tlog_likelihood:-8732169.09\n",
      "2016-02-14 22:49:49 INFO:AuthorTopicModel:[INIT] 45\telapsed_time:58.09\tlog_likelihood:-8728986.80\n",
      "2016-02-14 22:50:49 INFO:AuthorTopicModel:[INIT] 46\telapsed_time:60.09\tlog_likelihood:-8727756.31\n",
      "2016-02-14 22:51:51 INFO:AuthorTopicModel:[INIT] 47\telapsed_time:61.90\tlog_likelihood:-8726765.65\n",
      "2016-02-14 22:52:53 INFO:AuthorTopicModel:[INIT] 48\telapsed_time:61.55\tlog_likelihood:-8720959.99\n",
      "2016-02-14 22:53:54 INFO:AuthorTopicModel:[INIT] 49\telapsed_time:60.93\tlog_likelihood:-8718195.57\n"
     ]
    }
   ],
   "source": [
    "model = AuthorTopicModel(n_doc, n_voca, n_topic, n_author)\n",
    "model.fit(corpus, doc_author, max_iter=max_iter)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Print top 10 words for each topic"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "topic  0 algorithm,problem,time,model,function,bound,show,result,optimal,complexity\n",
      "topic  1 network,service,realtime,control,performance,application,paper,routing,traffic,packet\n",
      "topic  2 data,query,database,information,algorithm,rule,view,technique,document,structure\n",
      "topic  3 system,distributed,protocol,communication,application,message,file,paper,performance,network\n",
      "topic  4 learning,network,system,method,approach,task,paper,problem,model,neural\n",
      "topic  5 image,model,object,using,surface,motion,robot,algorithm,method,visual\n",
      "topic  6 parallel,program,performance,memory,data,processor,analysis,application,compiler,machine\n",
      "topic  7 system,design,software,language,application,paper,research,tool,object,support\n",
      "topic  8 agent,system,model,language,planning,logic,constraint,plan,action,paper\n",
      "topic  9 problem,method,algorithm,linear,function,result,paper,solution,technique,matrix\n"
     ]
    }
   ],
   "source": [
    "for k in range(n_topic):\n",
    "    top_words = get_top_words(model.TW, voca, k, 10)\n",
    "    print('topic ', k , ','.join(top_words))"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Plot topic distribution of random author"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "data": {
      "image/png": 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+8pUrZl0MaZdhSmhpB2Aa5MEW1oXG8LiQNC1TQkuSJEnLMDCWJEmSMDCWJEmSAANjSZIk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\nVn8IPKqqLhtulJ4OfIn3uo7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naPtwxrA8VXU2rSvRBbTr4oXMp0N/EuOvJUvty+vpbWra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\nWR42AAAAAElFTkSuQmCC\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0x11b188cf8>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "author_id = 7\n",
    "fig = plt.figure(figsize=(12,6))\n",
    "plt.bar(range(n_topic), model.AT[author_id]/np.sum(model.AT[author_id]))\n",
    "plt.title(author_name[author_id])\n",
    "plt.xticks(np.arange(n_topic)+0.5, ['\\n'.join(get_top_words(model.TW, voca, k, 10)) for k in range(n_topic)])\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "data": {
      "image/png": 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KATAAAAAqhQAYAAAAlUIADAAAgEohAAYAAEClEAADAACgUgiAAQAAUCkEwAAAAKgUAmAA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\nSUVORK5CYII=\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0x11d4b9240>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "author_id = 32\n",
    "fig = plt.figure(figsize=(12,6))\n",
    "plt.bar(range(n_topic), model.AT[author_id]/np.sum(model.AT[author_id]))\n",
    "plt.title(author_name[author_id])\n",
    "plt.xticks(np.arange(n_topic)+0.5, ['\\n'.join(get_top_words(model.TW, voca, k, 10)) for k in range(n_topic)])\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": []
  }
 ],
 "metadata": {
  "kernelspec": {
   "display_name": "Python 3",
   "language": "python",
   "name": "python3"
  },
  "language_info": {
   "codemirror_mode": {
    "name": "ipython",
    "version": 3
   },
   "file_extension": ".py",
   "mimetype": "text/x-python",
   "name": "python",
   "nbconvert_exporter": "python",
   "pygments_lexer": "ipython3",
   "version": "3.4.3"
  }
 },
 "nbformat": 4,
 "nbformat_minor": 0
}
